Case studies

Checkout Customization and Payment Rules Engine for a High Growth D2C Fashion Brand

Written by Leo Kaiser Anto | Jun 16, 2026 6:28:22 AM

 

Overview

 

In high growth ecommerce, acquisition often gets the spotlight. But for a rapidly scaling D2C fashion brand operating across UAE and Saudi Arabia, revenue leakage was happening much later in the funnel at checkout.

 

Despite strong traffic and healthy demand, the brand faced a 34 percent cart abandonment rate during checkout, significantly above regional benchmarks.

 

Analysis revealed the issue was not product or pricing but payment experience friction and lack of personalization.

 

The objective was to redesign checkout into a dynamic payment decisioning system capable of:

  • Reducing cart abandonment
  • Increasing prepaid conversions
  • Improving BNPL adoption
  • Controlling COD risk exposure
  • Optimizing checkout performance

 

The final solution introduced a Shopify Functions based Payment Rules Engine designed to personalize payment visibility in real time.

 

Problem Statements

 

  • High checkout abandonment rates
  • Cash on Delivery overexposure
  • Low prepaid order adoption
  • No payment personalization
  • High return to origin losses
  • Manual intervention for risky orders

 

The checkout experience remained static while customer behavior and risk continuously changed.

 

 

Challenges

 

Payment Preference Misalignment

 

Cash on Delivery appeared as the default payment method despite increasing customer preference for digital payment options.

  • Lower prepaid conversion
  • Reduced cash flow predictability
  • Higher checkout friction

 

Uncontrolled COD Risk

 

All customers had equal payment access regardless of behavioral signals.

  • 28 percent return to origin rate
  • Higher reverse logistics cost
  • Operational inefficiencies

 

Lack of Checkout Intelligence

 

  • No real-time payment evaluation
  • No customer segmentation
  • No dynamic payment visibility

 

 

Process

 

Step 1: Checkout Audit and Behavioral Analysis

 

The team evaluated:

  • Checkout drop-off points
  • Payment method performance
  • Customer behavior patterns
  • Conversion bottlenecks

 

Step 2: Shopify Functions Payment Rules Engine

 

Amwhiz implemented PayRules using Shopify Functions.

 

Payment methods were dynamically controlled using:

  • Customer tags
  • Cart value
  • Purchase history
  • Behavioral signals

 

Step 3: COD Risk Intelligence Layer

 

COD eligibility became conditional.

 

Restrictions applied to customers with:

  • Multiple previous RTO incidents
  • High return probability
  • Suspicious purchasing patterns

 

Step 4: BNPL Optimization Engine

 

Buy Now Pay Later options were prioritized for:

  • Orders above AED 200
  • Returning customers
  • Low risk customer profiles

 

Step 5: Time Based Rule Scheduling

 

Dynamic restrictions adjusted payment behavior during:

  • Post Eid periods
  • January refund cycles
  • Known high RTO windows

 

Step 6: Analytics and CRM Integration

 

The solution included:

  • PostgreSQL analytics tracking
  • Prisma optimization layer
  • HubSpot CRM integration
  • Conversion monitoring

 

How the System Worked

 

  • Customer profile evaluated
  • Cart value rules applied
  • Risk scoring executed
  • Payment methods ranked dynamically
  • COD enabled or restricted
  • BNPL prioritized
  • Transaction data logged

 

 

Benefits

 

Reduced Checkout Abandonment

  • 19 percent reduction in abandonment

 

Lower Financial Risk

  • 61 percent reduction in RTO losses

 

Higher Prepaid Adoption

  • 31 percent increase in prepaid orders

 

BNPL Growth

  • 2.8x increase in BNPL usage

 

Revenue Recovery

  • Recovered AED 1.2 million annually

 

Conclusion

 

Checkout is no longer simply a final purchase step. It has become a revenue optimization layer that influences conversion, payment quality, and operational efficiency.

 

By implementing a Shopify Functions based Payment Rules Engine, Amwhiz transformed checkout into a dynamic intelligence system that improved conversion while reducing financial risk.

 

 

Ready to Optimize Your Checkout Performance?

 

Amwhiz helps ecommerce brands build scalable checkout optimization systems including:

  • Shopify Functions implementation
  • Payment rule engines
  • BNPL optimization
  • Risk management automation

 

Email: sales@amwhiz.com

 

Phone: +91 91500 65500